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Emergent behaviors are in the focus of recent research interest. It is then of considerable importance to investigate what optimizations suit the learning and prediction of chaotic systems, the putative candidates for emergence. We have…

Machine Learning · Computer Science 2007-05-23 Z. Szabo , A. Lorincz

We consider a system of classical particles confined in a box $\Lambda\subset\mathbb{R}^d$ with zero boundary conditions interacting via a stable and regular pair potential. Based on the validity of the cluster expansion for the canonical…

Probability · Mathematics 2021-03-30 Giuseppe Scola

This paper proposes a differentiator for sampled signals with bounded noise and bounded second derivative. It is based on a linear program derived from the available sample information and requires no further tuning beyond the noise and…

Optimization and Control · Mathematics 2021-06-11 Hernan Haimovich , Richard Seeber , Rodrigo Aldana-López , David Gómez-Gutiérrez

Traditional measures of smoothness often fail to provide accurate $L_p$-error estimates for approximation by sampling or interpolation operators, especially for functions with low smoothness. To address this issue, we introduce a modified…

Numerical Analysis · Mathematics 2025-07-02 Yurii Kolomoitsev

We derive analytic formulas to reconstruct particle-averaged quantities from experimental results that suffer from the efficiency loss of particle measurements. These formulas are derived under the assumption that the probabilities of…

Data Analysis, Statistics and Probability · Physics 2025-10-17 Masakiyo Kitazawa , ShinIchi Esumi , Takafumi Niida , Toshihiro Nonaka

Mixed-dimensional elliptic equations exhibiting a hierarchical structure are commonly used to model problems with high aspect ratio inclusions, such as flow in fractured porous media. We derive general abstract estimates based on the theory…

Numerical Analysis · Mathematics 2022-04-21 Jhabriel Varela , Elyes Ahmed , Eirik Keilegavlen , Jan Martin Nordbotten , Florin Adrian Radu

In this paper, we study a class of two sample test statistics based on inter-point distances in the high dimensional and low sample size setting. Our test statistics include the well-known energy distance and maximum mean discrepancy with…

Methodology · Statistics 2020-04-13 Changbo Zhu , Xiaofeng Shao

We study the $L_p$-discrepancy of random point sets in high dimensions, with emphasis on small values of $p$. Although the classical $L_p$-discrepancy suffers from the curse of dimensionality for all $p \in (1,\infty)$, the gap between…

Numerical Analysis · Mathematics 2025-12-10 Erich Novak , Friedrich Pillichshammer

We prove a large deviations principle for the empirical law of the block sizes of a uniformly distributed non-crossing partition. As an application we obtain a variational formula for the maximum of the support of a compactly supported…

Probability · Mathematics 2011-07-04 Janosch Ortmann

Divergence functions are measures of distance or dissimilarity between probability distributions that serve various purposes in statistics and applications. We propose decompositions of Wasserstein and Cram\'er distances$-$which compare two…

Methodology · Statistics 2025-08-08 Johannes Resin , Daniel Wolffram , Johannes Bracher , Timo Dimitriadis

How predictable a word is can be quantified in two ways: using human responses to the cloze task or using probabilities from language models (LMs).When used as predictors of processing effort, LM probabilities outperform probabilities…

Computation and Language · Computer Science 2026-05-27 Sathvik Nair , Byung-Doh Oh

The problem of binary hypothesis testing between two probability measures is considered. New sharp bounds are derived for the best achievable error probability of such tests based on independent and identically distributed observations.…

Information Theory · Computer Science 2024-05-30 Valentinian Lungu , Ioannis Kontoyiannis

In master-field simulations of lattice QCD, the expectation values of interest are obtained from a single or at most a few representative gauge-field configurations on very large lattices. If the light quarks are included, the generation of…

High Energy Physics - Lattice · Physics 2020-06-12 Anthony Francis , Patrick Fritzsch , Martin Lüscher , Antonio Rago

The spherical cap discrepancy is a widely used measure for how uniformly a sample of points on the sphere is distributed. Being hard to compute, this discrepancy measure is typically replaced by some lower or upper estimates when designing…

Combinatorics · Mathematics 2020-12-21 Holger Heitsch , René Henrion

This paper is concerned with the problem of sampling and interpolation involving derivatives in shift-invariant spaces and the error analysis of the derivative sampling expansions for fundamentally large classes of functions. A new type of…

Functional Analysis · Mathematics 2024-02-15 Kumari Priyanka , A. Antony Selvan

Stochastic optimization techniques are standard in variational inference algorithms. These methods estimate gradients by approximating expectations with independent Monte Carlo samples. In this paper, we explore a technique that uses…

Machine Learning · Computer Science 2019-08-15 Mike Wu , Noah Goodman , Stefano Ermon

A behavior of one class of mappings with finite distortion at a neighborhood of the origin is investigated. There is proved a lower estimate of distortion of a distance under mappings mentioned above.

Complex Variables · Mathematics 2018-01-23 R. R. Salimov , E. A. Sevost'yanov , A. A. Markysh

The present status of lattice calculations of $f_D$, $f_B$ and some mass splittings are discussed. When one includes the uncertainties due to discretization errors, the results do not yet have a sufficient precision to be relevant to…

High Energy Physics - Lattice · Physics 2009-10-22 R. Sommer

In this paper we give an overview of recent results on (upper and lower) discrepancy estimates for (concrete) sequences in the unit-cube. In particular we also give an overview of discrepancy estimates for certain classes of hybrid…

Number Theory · Mathematics 2014-07-10 Gerhard Larcher

We characterize the best $L_{2}$ approximation to a multivariate function by linear combinations of ridge functions multiplied by some fixed weight functions. In the special case when the weight functions are constants, we propose explicit…

Classical Analysis and ODEs · Mathematics 2007-08-27 Vugar Ismailov